7  Quality Check: Processing AED. Empadronados

Author

Francisco Sanchez-Saez

Published

June 11, 2023

7.1 Input

The table to be analysed is aed.csv.

7.2 Check variables

The variables extracted from aed are: sip, fecha_registro, fecha_alta, dpto_cod, centro_cod, circ_alta_cod, circ_alta_desc, motivo_urg_cod, motivo_urg_desc, diag_cod, diag2_cod, prioridad_cod, prioridad_desc, tipo_codigo1, and tipo_codigo2.

7.2.1 Check mandatory vars

All mandatory vars are present.

7.2.2 Check all vars

fecha_alta_admin, dpto_desc, centro_desc, diag_desc, and diag2_desc were not extracted.

7.2.3 Completeness

In Figure 7.1 is shown the percentage of non-missing values for each variable. Non-mandatory variables are shown at the bottom of the figure.


Figure 7.1: Variables completeness


7.3 Check content

The aed table has a total of n = 7 ‍142 ‍464 observations.

7.3.1 Population

  • In aed table there are 1 ‍241 ‍653 distinct individuals. All the individuals are included in the target population. Therefore, there are 1 ‍241 ‍653 individuals included in the target population out of the 1 ‍842 ‍818 total individuals in the cohort. These represents 67.38% of the total.
  • The Table 7.1 shows the number of individuals per year of the study period.


Table 7.1: Number of individuals per year of calculation
Year of admission Count of distinct individuals
2009 300284
2010 280111
2011 279791
2012 256086
2013 271501
2014 285637
2015 330202
2016 344792
2017 344593
2018 342717
2019 352752
2020 287026
2021 326614
2022 200


7.3.2 Date of the admission

The variable fecha_registro is missing in 0 observations, so it is 100% complete. The minimum and maximum date are 2009-01-01 and 2022-01-01 respectively. Table 7.2 shows the number of admissions per year of fecha_registro.

There are dates outside the study period. From the non-missing dates:

  • 100% are inside the study period.

  • 0% occurred before the start of the study period.

  • 0% occurred after the end of the study period.


Table 7.2: Number of admissions each year of calculation
Year of the admission Count
2009 530703
2010 496300
2011 490872
2012 454297
2013 480004
2014 512651
2015 594314
2016 628301
2017 624208
2018 621110
2019 640362
2020 492889
2021 576250
2022 203


The month and year with less admissions was January 2022 with n = 203 and the month and year with more admissions was July 2021 with n = 57648.

In Figure 7.2, Figure 7.3, and Figure 7.4 are presented the frequencies of years, months, and days of the admissions respectively.


Figure 7.2: Admission year


Figure 7.3: Admission month


Figure 7.4: Admission day


7.3.3 Date of the discharge

The variable fecha_alta is missing in 1028167 observations, so it is 85.6% complete. The minimum and maximum date are 2009-01-01 and 2022-03-24 respectively. Table 7.3 shows the number of discharges per year of fecha_alta.

There are dates outside the study period. From the non-missing dates:

  • 100% are inside the study period.

  • 0% occurred before the start of the study period.

  • 0% occurred after the end of the study period.


Table 7.3: Number of discharges each year of calculation
Year of the discharge Count
2009 221696
2010 298642
2011 369416
2012 396751
2013 396434
2014 481902
2015 566635
2016 596556
2017 599233
2018 580852
2019 607696
2020 462936
2021 535284
2022 264
NA 1028167


The month and year with less discharges was February 2022 with n = 1, March 2022 with n = 1 and the month and year with more discharges was NA NA with n = 1028167.

In Figure 7.5, Figure 7.6, and Figure 7.7 are presented the frequencies of years, months, and days of the visits respectively.


#> Warning: Removed 1 rows containing missing values (`position_stack()`).

Figure 7.5: Discharge year


Figure 7.6: Discharge month


#> Warning: Removed 1 rows containing missing values (`position_stack()`).

Figure 7.7: Discharge day


7.3.4 Visit service

The variable motivo_urg_desc is missing in 0 observations, so it is 100% complete. Table 7.4 shows all the services used in the primary care visits arranged by alphabetic order. Figure 7.8 shows the count of the utilization of each visit service. Finally, Figure 7.9 shows the count of visits for the 10 most used services per year.


Table 7.4: Healths services used in the emergency deoartment visits
Service Count Percentage
Accidente casual 660352 9.25%
Accidente de trabajo 66408 0.93%
Accidente de tráfico 159141 2.23%
Agresión 48185 0.67%
Autolesión 17667 0.25%
COVID-sospecha 50453 0.71%
Caso Relacionado con Gripe A 2658 0.04%
Enfermedad común 5524973 77.35%
Otras causas 584057 8.18%
[Sin referencia] 28552 0.40%
[Vacío] 18 0.00%


Figure 7.8: Primary care visit services


Figure 7.9: Most used primary care visit services per year


7.3.5 Diagnoses codes: diag_cod

The variable diag_cod is missing in 0 observations, so it is 100% complete. Figure 7.10 shows the most employed diagnoses codes. Finally, Figure 7.11 shows the count of the 10 most employed codes per year.


Figure 7.10: Diagnosis codes (diag_cod) used in specialist visits


Figure 7.11: Diagnosis codes (diag_cod) used in specialist visits per year


7.3.6 Diagnoses codes: diag2_cod

The variable diag2_cod is missing in 0 observations, so it is 100% complete. Figure 7.10 shows the most employed diagnoses codes. Finally, Figure 7.11 shows the count of the 10 most employed codes per year.


Figure 7.12: Diagnosis codes (diag2_cod) used in specialist visits


Figure 7.13: Diagnosis codes (diag2_cod) used in specialist visits per year


7.3.7 Code vocabulary: tipo_codigo1

The variable tipo_codigo1 is missing in 0 observations, so it is 100% complete. Figure 7.14 shows the count of the utilization of each visit service. Finally, Figure 7.15 shows the count of visits for the 10 most used services per year.


Figure 7.14: Code (diag_cod) vocabularies used in specialist visits


Figure 7.15: Code (diag_cod) vocabularies used in specialist visits per year


7.3.8 Code vocabulary: tipo_codigo2

The variable tipo_codigo2 is missing in 0 observations, so it is 100% complete. Figure 7.16 shows the count of the utilization of each visit service. Finally, Figure 7.17 shows the count of visits for the 10 most used services per year.


Figure 7.16: Code (diag2_cod) vocabularies used in specialist visits


Figure 7.17: Code (diag2_cod) vocabularies used in specialist visits per year